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Genetic-diversity-and-interaction-between-the-maintainers-of-commercial-Soybean-cultivars-using-self/
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Bem-vindo! Este repositório reúne código, dados e relatórios reprodutíveis associados ao artigo publicado na Crop Science:
Costa, W.G., et al. (2025). Genetic diversity and interaction
between the maintainers of commercial Soybean cultivars using selfing.
Crop Science.
DOI: 10.1002/csc2.20816
O objetivo é avaliar a diversidade genética e a interação entre mantenedores de cultivares comerciais de soja, utilizando Random Forest, Análise de Correspondência Múltipla (MCA) e Mapas Auto-Organizáveis de Kohonen (SOM).
flowchart TD
A[Input Data<br/>Morphological descriptors, maintainers] --> B[Random Forest<br/>Variable selection]
B --> C[MCA<br/>Dimensionality reduction]
C --> D[SOM<br/>Clustering maintainers]
D --> E[Results & Visualizations<br/>Diversity patterns, trait distributions, productivity trends]Este trabalho faz parte do artigo publicado em Crop
Science:
👉 Link para o
artigo
Este projeto integra as atividades do LICAE (Laboratório de Inteligência Computacional e Aprendizado Estatístico) da UFV, especializado em inteligência computacional, aprendizado de máquina e modelagem estatística aplicados a problemas complexos em agronomia, genética e ciências biológicas.
Clone o repositório:
git clone https://github.com/WevertonGomesCosta/Genetic-diversity-and-interaction-between-the-maintainers-of-commercial-Soybean-cultivars-using-self.gitInstale as dependências em R:
install.packages(c("tidyverse", "FactoMineR", "factoextra", "randomForest", "kohonen"))Rode o pipeline principal em RMarkdown.
Contribuições são bem-vindas via:
- Issues para discussão de melhorias
- Pull requests para correções
- Sugestões de extensões metodológicas
Este trabalho está licenciado sob CC BY-NC-SA
4.0.
Para uso comercial ou modificações significativas, contate os
autores.
Welcome! This repository contains code, data, and reproducible reports associated with the article published in Crop Science:
Costa, W.G., et al. (2025). Genetic diversity and interaction
between the maintainers of commercial Soybean cultivars using selfing.
Crop Science.
DOI: 10.1002/csc2.20816
The goal is to evaluate genetic diversity and interaction among maintainers of commercial soybean cultivars, using Random Forest, Multiple Correspondence Analysis (MCA), and Self-Organizing Maps (SOM).
flowchart TD
A[Input Data<br/>Morphological descriptors, maintainers] --> B[Random Forest<br/>Variable selection]
B --> C[MCA<br/>Dimensionality reduction]
C --> D[SOM<br/>Clustering maintainers]
D --> E[Results & Visualizations<br/>Diversity patterns, trait distributions, productivity trends]This work is part of the article published in Crop
Science:
👉 Link to the
article
This project is part of the activities of the LICAE (Laboratory of Computational Intelligence and Statistical Learning) at UFV, specialized in computational intelligence, machine learning, and statistical modeling applied to complex problems in agronomy, genetics, and biological sciences.
Clone the repository:
git clone https://github.com/WevertonGomesCosta/Genetic-diversity-and-interaction-between-the-maintainers-of-commercial-Soybean-cultivars-using-self.gitInstall dependencies in R:
install.packages(c("tidyverse", "FactoMineR", "factoextra", "randomForest", "kohonen"))Run the main RMarkdown pipeline.
Contributions are welcome via:
- Opening issues for improvement discussions
- Submitting pull requests for fixes
- Suggesting methodological extensions
This work is licensed under CC BY-NC-SA
4.0.
For commercial use or significant modifications, please contact the
authors.
sessionInfo()R version 4.5.1 (2025-06-13 ucrt)
Platform: x86_64-w64-mingw32/x64
Running under: Windows 11 x64 (build 26100)
Matrix products: default
LAPACK version 3.12.1
locale:
[1] LC_COLLATE=Portuguese_Brazil.utf8 LC_CTYPE=Portuguese_Brazil.utf8
[3] LC_MONETARY=Portuguese_Brazil.utf8 LC_NUMERIC=C
[5] LC_TIME=Portuguese_Brazil.utf8
time zone: America/Sao_Paulo
tzcode source: internal
attached base packages:
[1] stats graphics grDevices utils datasets methods base
loaded via a namespace (and not attached):
[1] vctrs_0.6.5 cli_3.6.5 knitr_1.50 rlang_1.1.6
[5] xfun_0.53 stringi_1.8.7 promises_1.3.3 jsonlite_2.0.0
[9] workflowr_1.7.2 glue_1.8.0 rprojroot_2.1.1 git2r_0.36.2
[13] htmltools_0.5.8.1 httpuv_1.6.16 sass_0.4.10 rmarkdown_2.29
[17] evaluate_1.0.5 jquerylib_0.1.4 tibble_3.3.0 fastmap_1.2.0
[21] yaml_2.3.10 lifecycle_1.0.4 whisker_0.4.1 stringr_1.5.2
[25] compiler_4.5.1 fs_1.6.6 Rcpp_1.1.0 pkgconfig_2.0.3
[29] rstudioapi_0.17.1 later_1.4.4 digest_0.6.37 R6_2.6.1
[33] pillar_1.11.1 magrittr_2.0.4 bslib_0.9.0 tools_4.5.1
[37] cachem_1.1.0 Weverton Gomes da Costa, Doutorando, Pós-Graduação em Genética e Melhoramento - Universidade Federal de Viçosa, wevertonufv@gmail.com↩︎